Employment Opportunities and Experiences among Recent Master’s-Level Global Health Graduates
Bibliographic record
Abstract
OBJECTIVES: To examine the job search, employment experiences, and job availability of recent global health-focused master's level graduates. METHODS: An online survey was conducted from October to December 2016 based out of Washington, DC. The study sample includes students graduating with master's degrees in global health, public health with a global health concentration or global medicine from eight U.S. universities. RESULTS: Out of 256 potential respondents, 152 (59%) completed the survey, with 102/152 (67%) employed. Of unemployed graduates, 38% were currently in another educational training program. Out of 91 employed respondents, 62 (68%) reported they had limitations or gaps in their academic training. The average salary of those employed was between $40,000 and $59,000 annually. The majority of respondents reported they currently work in North America (83.5%.); however, only 31% reported the desire to work in North America following graduation. CONCLUSIONS: Discrepancies exist between graduates' expectations of employment in global public health and the eventual job market. Communication between universities, students and employers may assist in curriculum development and job satisfaction for the global public health workforce.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".